4 papers · 1 filter
Belief-Calibrated Optimization: An Explicit World Model for Agentic Optimization
Yuhan Chen, Zhihua Tian, Mahavir Dabas +7
The performance of an LLM agent depends on the scaffold around a frozen model. A common way to improve that scaffold is to use a coding agent as an optimizer: it reads current scor…
Can Generalist Agents Automate Data Curation?
Feiyang Kang, Hanze Li, Adam Nguyen +5
Curating training data is among the most consequential yet labor-intensive parts of modern AI development: practitioners iteratively propose, implement, evaluate, and revise data p…
Memory-Induced Tool-Drift in LLM Agents
Mahavir Dabas, Jihyun Jeong, Ming Jin +1
LLM agents increasingly combine long-term memory for personalization with tool calling for taking actions. We study a failure of this combination: personality-driven preferences st…
Characterizing Model-Native Skills
Feiyang Kang, Mahavir Dabas, Myeongseob Ko +1
Skills are a natural unit for describing what a language model can do and how its behavior can be changed. However, existing characterizations rely on human-written taxonomies, tex…